Outcome-based software-defined infrastructure

ABSTRACT

A method and system for outcome-based adjustment of a software-defined environment (SDE) that includes establishing a link between a business outcome and a first resource configuration from software defined environment, establishing a monitoring mechanism for continuously measuring a current state of the SDE, using a behavior model of the SDE to anticipate, or forecast, a triggering event, and responsive to the forecast of a triggering event, using the behavior model to determine a second resource configuration to achieve the business outcome. The link includes at least one of a utility of services for the business outcome, a cost of a set of resources consumed by the first resource configuration, and a risk of the set of resources becoming unavailable.

BACKGROUND OF THE INVENTION

The present invention relates generally to the field of software-definedenvironments (SDE), and more particularly to workload processing in anSDE.

Enterprises are increasingly aggressive in moving mission-critical andperformance-sensitive applications to heavily virtualized environmentson shared infrastructure and cloud. Mobile, social, and analyticsapplications are oftentimes directly developed and operated on sharedinfrastructure and cloud. Current virtualization and cloud solution onlyallow basic abstraction of the computing, storage, and network resourcesin terms of their capacity. This approach often calls forstandardization of the underlying system architecture to simplify theabstraction of these resources.

Further, the workload-optimized system approach often calls for tightintegration of the workload (including compiler) to the underlyingsystem architecture. This approach allows direct leverage of the specialcapabilities offered by each micro-architecture and by the system levelcapabilities at the expense of labor intensive optimization required.

A framework, referred to herein as the “Pfister framework,” has beenused to describe workload characteristics of a given application. ThePfister framework considers “thread contention” versus “datacontention.” With that in mind, four workload categories are defined:(i) mixed workload updating shared data or queues (such as enterprisesoftware, also known as application and integration middleware); (ii)highly threaded applications; (iii) parallel data structures withanalytics (such as frameworks for storage and large-scale processing ofdata sets on cluster computing environments); and (iv) small discreteapplications.

SUMMARY

According to an aspect of the present invention, there is a method foroutcome-based adjustment of a software-defined environment (SDE) thatincludes establishing a link between a business outcome and a firstresource configuration from software defined environment, establishing amonitoring mechanism for continuously measuring a current state of theSDE, using a behavior model of the SDE to anticipate, or forecast, atriggering event, and responsive to the forecast of a triggering event,using the behavior model to determine a second resource configuration toachieve the business outcome. The link includes at least one of autility of services for the business outcome, a cost of a set ofresources consumed by the first resource configuration, and a risk ofthe set of resources becoming unavailable. At least the using thebehavior model steps are performed by computer software running oncomputer hardware.

According to an aspect of the present invention, there is a computerprogram product for outcome-based adjustment of a software-definedenvironment (SDE), the computer program product includes a computerreadable storage medium having stored thereon program instructionsprogrammed to establish a link between a business outcome and a firstresource configuration from a software defined environment, establish amonitoring mechanism for continuously measuring a current state of theSDE, use a behavior model of the SDE to forecast a triggering event, andresponsive to a forecast of the triggering event, use the behavior modelto determine a second resource configuration to achieve the businessoutcome. The link includes at least one of a utility of services for thebusiness outcome, a cost of a set of resources consumed by the firstresource configuration, and a risk of the set of resources becomingunavailable.

According to an aspect of the present invention, there is a computersystem for outcome-based adjustment of a software-defined environment(SDE), the computer system including a processor(s) set, and a computerreadable storage medium. The processor set is structured, located,connected, and/or programmed to run program instructions stored on thecomputer readable storage medium and the program instructions includeprogram instructions programmed to establish a link between a businessoutcome and a first resource configuration from a software definedenvironment, establish a monitoring mechanism for continuously measuringa current state of the SDE, use a behavior model of the SDE to forecasta triggering event, and responsive to a forecast of the triggeringevent, use the behavior model to determine a second resourceconfiguration to achieve the business outcome. The link includes atleast one of a utility of services for the business outcome, a cost of aset of resources consumed by the first resource configuration, and arisk of the set of resources becoming unavailable.

According to an aspect of the present invention, there is a method thatincludes determining a business operation and a corresponding set oftasks to be performed in a software defined environment (SDE),establishing a first resource configuration to perform the correspondingset of tasks to achieve a business outcome target, determining a firstresource cost for performing the corresponding set of tasks, monitoringthe SDE to identify a triggering event, responsive to identifying thetriggering event, establishing a second resource configuration toaddress the triggering event, and determining a second resource cost forperforming the corresponding set of tasks according to the secondresource configuration. At least the monitoring and establishing asecond resource configuration steps are performed by computer softwarerunning on computer hardware.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing node used in a first embodiment of asystem according to the present invention;

FIG. 2 depicts an embodiment of a cloud computing environment (alsocalled the “first embodiment system”) according to the presentinvention;

FIG. 3 depicts abstraction model layers used in the first embodimentsystem;

FIG. 4 is a flowchart showing a first embodiment method performed, atleast in part, by the first embodiment system;

FIG. 5 is a block diagram view of a machine logic (for example,software) portion of the first embodiment system;

FIG. 6 is a flowchart view of a second embodiment of a method accordingto the present invention;

FIG. 7 is a graph view showing information that is generated by and/orhelpful in understanding embodiments of the present invention;

FIG. 8 is a system view of second embodiment of a system according tothe present invention; and

FIG. 9 is a flowchart view of a third embodiment of a method performed,at least in part, by the second embodiment system.

DETAILED DESCRIPTION

The utility function of a software defined environment (SDE) iscontinuously adjusted responsive to continuous monitoring of the SDE interms of value created, minus the cost of resources associated with thevalue creation, and the cost associated with the risk of failure. Thepresent invention may be a system, a method, and/or a computer programproduct. The computer program product may include a computer readablestorage medium (or media) having computer readable program instructionsthereon for causing a processor to carry out aspects of the presentinvention.

The computer readable storage medium is a tangible device that retainsand/or stores instructions for use by an instruction execution device.The computer readable storage medium may be, for example, but is notlimited to, an electronic storage device, a magnetic storage device, anoptical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein are, accordingto some embodiments, downloaded to respective computing/processingdevices from a computer readable storage medium or to an externalcomputer or external storage device via a network, for example, theInternet, a local area network, a wide area network and/or a wirelessnetwork. The network comprise copper transmission cables, opticaltransmission fibers, wireless transmission, routers, firewalls,switches, gateway computers and/or edge servers. A network adapter cardor network interface in each computing/processing device receivescomputer readable program instructions from the network and forwards thecomputer readable program instructions for storage in a computerreadable storage medium within the respective computing/processingdevice.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, are implemented bycomputer readable program instructions.

The computer readable program instructions are, according to someembodiments of the present invention, provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. The computer readable program instructions mayalso be stored in a computer readable storage medium that directs acomputer, a programmable data processing apparatus, and/or other devicesto function in a particular manner, such that the computer readablestorage medium having instructions stored therein comprises an articleof manufacture including instructions which implement aspects of thefunction/act specified in the flowchart and/or block diagram block orblocks.

The computer readable program instructions are, according to someembodiments of the present invention, loaded onto a computer, otherprogrammable data processing apparatus, or other device to cause aseries of operational steps to be performed on the computer, otherprogrammable apparatus or other device to produce a computer implementedprocess, such that the instructions which execute on the computer, otherprogrammable apparatus, or other device implement the functions/actsspecified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams represents a module, segment, or portion ofinstructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block occur out of the ordernoted in the figures. For example, two blocks shown in succession may,in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, are, in someembodiments, implemented by special purpose hardware-based systems thatperform the specified functions or acts or carry out combinations ofspecial purpose hardware and computer instructions.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that arerapidly provisioned and released with minimal management effort orinteraction with a provider of the service. For some embodiments of thepresent invention, this cloud model includes at least fivecharacteristics, at least three service models, and at least fourdeployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources, but may be able to specify location at a higherlevel of abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities are rapidly and elastically provisioned,in some cases automatically, to quickly scale out and rapidly releasedto quickly scale in. To the consumer, the capabilities available forprovisioning often appear to be unlimited and can be purchased in anyquantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage ismonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which includes, in some embodiments, operatingsystems and applications. The consumer does not manage or control theunderlying cloud infrastructure but has control over operating systems,storage, deployed applications, and possibly limited control of selectnetworking components (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It is managed by the organization or a third party andexists either on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It is managed by the organizations or a third party andexists either on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities, butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting for loadbalancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that are suitablefor use with computer system/server 12 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, handheld or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12, according to some embodiments of thepresent invention, are practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 include, but are not limited to,one or more processors or processing units 16, a system memory 28, and abus 18 that couples various system components including system memory 28to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 include computer system readable media in the form ofvolatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 further includes, in someembodiments, other removable/non-removable, volatile/non-volatilecomputer system storage media. By way of example only, storage system 34is provided for reading from and writing to a non-removable,non-volatile magnetic media (not shown and typically called a “harddrive”). By further example, and although not shown, a magnetic diskdrive for reading from and writing to a removable, non-volatile magneticdisk (e.g., a “floppy disk”), and an optical disk drive for reading fromor writing to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media are provided. In such instances, each canbe connected to bus 18 by one or more data media interfaces. As will befurther depicted and described below, memory 28 includes, in someembodiments, at least one program product having a set (e.g., at leastone) of program modules that are configured to carry out the functionsof embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,is stored in memory 28 by way of example, and not limitation, as well asan operating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 also, according to some embodiments of thepresent invention, communicates with one or more external devices 14such as a keyboard, a pointing device, a display 24, etc.; one or moredevices that enable a user to interact with computer system/server 12;and/or any devices (e.g., network card, modem, etc.) that enablecomputer system/server 12 to communicate with one or more othercomputing devices. Such communication occurs, in some embodiments, viaInput/Output (I/O) interfaces 22. Still yet, computer system/server 12communicates, in some embodiments, with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 20. As depicted,network adapter 20 communicates with the other components of computersystem/server 12 via bus 18. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system/server 12. Examples include, but arenot limited to: microcode, device drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N, may communicate. Nodes 10 maycommunicate with one another. They are grouped (not shown) physically orvirtually, in one or more networks, such as Private, Community, Public,or Hybrid clouds as described hereinabove, or a combination thereof.This allows cloud computing environment 50 to offer infrastructure,platforms, and/or software as services for which a cloud consumer doesnot need to maintain resources on a local computing device. It isunderstood that the types of computing devices 54A-N shown in FIG. 2 areintended to be illustrative only and that computing nodes 10 and cloudcomputing environment 50 communicate with any type of computerizeddevice over any type of network and/or network addressable connection(e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; storage devices 60 a;networks and networking components. Examples of software componentsinclude network application server software, in one example IBMWebSphere® application server software; and database software, in oneexample IBM DB2® database software. (IBM, zSeries, pSeries, xSeries,BladeCenter, WebSphere, and DB2 are trademarks of International BusinessMachines Corporation registered in many jurisdictions worldwide).

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities are provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 provides the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources comprise application softwarelicenses. Security (not shown) provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 66 provides examples of functionality for which thecloud computing environment is utilized. Examples of workloads andfunctions which are provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and functionality, according to the present invention (seefunction block 66 a) as will be discussed in detail, below, in thefollowing sub-sections of this Detailed description section.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The terminology used herein was chosen to best explain the principles ofthe embodiment, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

FIG. 4 shows flowchart 450 depicting a method according to the presentinvention. FIG. 5 shows program 500 for performing at least some of themethod steps of flowchart 450. This method and associated software willnow be discussed, over the course of the following paragraphs, withextensive reference to FIG. 4 (for the method step blocks) and FIG. 5(for the software blocks). As shown in FIG. 5, one exemplary physicallocation where program 500 is stored is in storage block 60 a (see FIG.3).

Processing begins at step S402, where outcome module (“mod”) 502identifies a business outcome target. In this example, the businessoutcome target is one, or more, business operations that are associatedwith certain requirements and/or expectations of profitability or othersuccessful end.

Processing proceeds to step S404, where task mod 504 determines a set oftasks to reach the outcome target. Oftentimes, multiple tasks areperformed to complete the identified business operation, or achieve thebusiness outcome target.

Processing proceeds to step S406, where performance indicator mod 506determines the set of performance indicator(s) for each task within theset of tasks determined in step S404. The quality or satisfactorycompletion of a given task that corresponds to a business operation ismeasured according to the level of performance achieved. Performanceindicators and their corresponding satisfactory levels are taskspecific. That is, each task typically has a set of performanceindicator(s) that is unique among other tasks. One example of aperformance indicator is a “key performance indicator,” or KPI. Examplesand further discussion of KPIs are provided in next sub-section of thedetailed description.

Processing proceeds to step S408, where outcome link mod 508,establishes outcome links between the task(s) of a given businessoperation and the business outcome target. The outcome links operate toprioritize the various tasks associated with the business operation. Inthat way, the higher priority task may be favored for achieving aparticular performance level over a lower priority task. This providesfor trade-off decisions to be made in the steps that follow foroptimizing the business outcome and continuously maintaining a targetoutcome.

Processing proceeds to step S410, where SDE (software definedenvironment) status mod 510 determines an SDE status. The term statusrefers to the performance level of the SDE for achieving the businessoutcome. The SDE status, as discussed in more detail below, includes:(i) the value to the business if the services are completed; (ii) thecost of the resource provisioning; (iii) the cost of a resource as thecost evolves during execution of the service(s); and/or (iv) the cost ofpotential failure (e.g. operational risk).

Processing proceeds to step S412, where course of action mod 512analyzes the SDE status to determine a course of action(s). The actionsthat may be taken are discussed in more detail below in the sub-sectionthat follows. These actions are designed to improve the overall utilityfunction of the system, whether at the user's utility function or theresource cost function. Course of action decisions are facilitated bythe SDE where the abstracted compute, storage, and network allow for aunified switch fabric for agile system optimization.

Processing proceeds to step S414, where monitor performance mod 514monitors the SDE status while taking the course of action(s) determinedin step S412. Monitoring acts to identify triggers, discussed below, fortaking a new course of action. Triggers include: (i) a request by theservice; (ii) a request by the workload; (iii) deviation of the observedperformance indicators of the business operation from the specifiedtolerance(s); and/or (iv) the occurrence of potential catastrophicevents. In summary, this monitoring step acts to monitor the valuecreation and cost of resource usage and the cost associated with therisk.

Processing proceeds to decision step S416, where monitor performance mod514 determines whether to adjust the SDE to better achieve the desiredbusiness outcome. The decision step provides for continuous optimizationof the utility function of the SDE in terms of value created, minus thecost of resources associated with the value creation, as well as thecost associated with the risk of failure. So long as a new course ofaction is not needed, or otherwise undesirable, processing follows the“no” branch, returning to step S414. When a new course of action isneeded, processing follows the “yes” branch to step S418.

Following the “yes” branch, processing proceeds to step S418, whereadjustment module 518 adjusts the SDE to achieve the business outcometarget. In this example, the adjustment module adjusts the resourceconfiguration so that the projected utility is continuously maximized.Alternatively, the adjustment module adjusts, as permitted, any of thevarious aspects of the overall utility function to optimize the businessoutcome. As shown in the illustration, upon adjustment in step S418,processing returns to step S414, where the SDE is further monitored.Alternatively, processing ends at step S418, having made a singleadjustment to reach a business outcome target.

Some embodiments of the present invention recognize the following facts,potential problems, and/or potential areas for improvement with respectto the current state of the art: (i) there is a shift of the valueproposition of cloud computing from that of cost reduction tosimultaneous agility and optimization; (ii) oftentimes, the IaaS(infrastructure as a service) providers need to know, from the users,the exact amount of resources needed before provisioning those resource,in that way, they can only do a limited amount of scaling, which isconventionally based on the load instead of business need; (iii)conventionally, it is entirely up to the user to conduct the tradeoffdetermination among different infrastructure resource requirements inorder to achieve the desired business outcome; and/or (iv) the businessrequirements of agility and optimization are drivers of software definedcomputing, where the entire computing infrastructure including compute,storage, and network are both: (a) software defined, and (b) dynamicallyprogrammable.

Software defined computing originated from the compute environment wherethe computing resources are virtualized and managed as virtual machines.The software defined network moves the network control plane away fromthe switch to the software running on a server for improvedprogrammability, efficiency, and extensibility. Software definedstorage, similar to software defined network, separates the controlplane from the data plane of a storage and dynamically leveragesheterogeneity of storage to respond to changing workload demands.Software defined environment (SDE) brings together software definedcompute, network, and storage, unifying the control planes from eachindividual software defined component. Unified control planes allow forrich resource abstractions to enable assembling purpose fit systemsand/or providing programmable infrastructures to enable dynamicoptimization in response to business requirements.

Some embodiments of the present invention provide for achievingoptimality of a SDE to offer flexibility and re-configurability withoutsacrificing agility. Some embodiments of the present invention providefor dynamically adjusting the overall SDE in response to a shifting ofworkloads between process-centric and data-centric workloads. Also, someembodiments of the present invention ensure the effectiveness of theoverall SDE, as it relates to a given target business outcome.

Some embodiments of the present invention perform one, or more of thefollowing steps: (i) establish the linkage between the business outcomeand the required support from the SDE, including: (a) the utility of theservices for the business, (b) the cost of resources consumed, and (c)the risk if the resources become unavailable due to data center outage,cyber-attacks, and/or cascading failures; (ii) capture the range offeasible tradeoff among different criteria in order to achieve therequired “outcome” from the SDE; (iii) establish the monitoringmechanisms for continuously measuring the current state of the SDE; (iv)use the behavior models for the SDE (that includes for the workload, thesystem, and the users) to anticipate, or forecast, the near futureevent, and, further, to conduct “what-if” analysis for selecting thebest courses of action going forward; and/or (v) continuously optimizethe configuration of the computing environment including: (a) optimaltiering of the data and compute infrastructure, (b) placement of theprocessing infrastructure, and/or (c) automatic scaling and/or migratingof the compute, storage, and network resources.

FIG. 6 illustrates process flow 600, where business operation 602 isdecomposed into multiple tasks 604 a, 604 b through 604 n. Each taskincludes respectively corresponding key performance indicators (KPIs),such as KPI set 605 for task 604 a. KPI set 605 includes the followingKPIs: confidentiality 606 a, integrity 608 a, availability 610 a,correctness (or precision) 612 a, and quality of service (QOS) 614 a(examples of QoS are latency and throughput). Note that the KPIsidentified in KPI set 605 are only an example selection of KPIs that maybe identified as known by those skilled in the art. In this example,each of the KPIs for each of the tasks is assigned a priority value.

The following use case is provided to clarify the operation of someembodiments of the present invention. An e-commerce business operationincludes the tasks: (i) marketing (ad display); (ii) search against thecatalog; (iii) verification of inventory; (iv) invoicing and billing;and (v) fulfillment. Each of these tasks are measured by a different setof KPIs. That is, marketing may focus on the KPI availability,search-against-the-catalog may focus on the KPIs latency and precision,and verification-of-inventory may focus on the KPI integrity.

Some embodiments of the present invention provide for each task toaccess data, both streamed and persisted, even when the persisted datais be located “outside” of the SDE. For persisted data located outsideof the SDE, the data is modeled as data node(s) at the edge of the SDE.

An objective for outcome-based optimization of business operations is toensure optimal business operation during both normal operation (to getthe most out of available resource) and abnormal operation (to ensurethe business operation continues despite actual or potential systemoutages). This objective sets up the potential requirement of tradeoffsamong various KPIs in order to ensure the overall business performancedoes not fail due to system outages. Continuing with the above example,it will be appreciated that tradeoff decisions are available as-neededwhen: (i) decomposing the business operation into tasks; (ii)prioritizing each task; and/or (iii) assigning KPIs for each of task.Using the task, “search against catalog” as an example, the value of theKPI “precision” may be reduced when there is an insufficient capacityuntil either the capacity is increased or the workload is reduced.

FIG. 7 illustrates in chart 700 how continuous optimizations, identifiedas resilient computing 702, with respect to business objectives,performs versus conventional system 704, when faced with a potentialsetback due to catastrophic event 706, such as a computer crash or cyberattack. In the chart, time 708 is on the x-axis and business performance710 is on the y-axis. Also illustrated are lines depicting theoreticaloptimum 712 and critical functionality 714 levels of businessperformance. The outcome of the business operation may be determinedaccording to, for example: (i) the priority of a certain task (P_(i));(ii) the relative importance of a specific KPI of the task (W_(ij))(importance of property “j” to task “I”); and/or (iii) the level ofachievement with respect to that specific key performance indicator(V_(ij)) (degree to which property “j” is achieved for task “i.”). Inthis example, each of the identified outcome determinant factors ispresented in the following formula:

Business Performance=ΣP_(i)ΣW_(ij)V_(ij)

Some embodiments of the present invention associate outcome-basedoptimization with establishing a “utility function” of the targetbusiness operation. The utility function may take into account: (i) thevalue to the business if the services are completed as described above;(ii) the cost of the resource provisioning (including usage of compute,storage, and network resources, as well as the software licensing cost,if any); (iii) the cost of a resource could evolve during execution ofthe services (this could be due to the type of resource(s) requirementchange and/or the place for best executing a process change); and/or(iv) the cost of potential failure due to system outage, data centeroutage, cascading failures, cyber attacks, and so forth (this is oftenreferred to as operational risk).

An outcome-optimized view of resource provisioning includes bothprocess-centric and data-centric views of overall business operations.The resources for storing data may be known (in terms of where).Provisioning the remaining resources may be determined according towhether it is more cost effective to move processing (e.g. migrate thevirtual images) to a location close to the data storage, or to move thedata to a location close to where processing capabilities, such asadvanced processing, reside. Consideration should include networkbandwidth availability. The problem of planning, placement, andprovisioning may be compared to the problem of scheduling an airlinecrew, where there is a need to either migrate the crew (i.e. data) orthe airplane (i.e. virtual images) for an optimal outcome. The dualitybetween the process, the images, and the data also allows for theintroduction of local caching of images and/or data (similar to thecontent delivery network concept) to maximize the effective throughputand minimize potential latency.

Some embodiments of the present invention translate the KPIs for a giventask to KPIs for the architecture and/or the infrastructure. In oneembodiment, the translation is as follows: (i) confidentialitytranslates to required isolation for the infrastructure; (ii)availability translates into redundant instantiation of the run time foreach task (active-active, active-passive, or based on implementationsimilar to Google File System (GFS) or Apache zookeeper); (iii)transaction, data, process, and policy integrity are each managed at theapplication level, while the integrity of the executables (and virtualmachine images) is managed at the infrastructure level; (iv) correctnessand/or precision are managed at the application level; and (v) QoStranslates directly to the implications for infrastructures. (Note: theterm(s) “Google,” “GPS,” and/or “Apache” may be subject to trademarkrights in various jurisdictions throughout the world and are used hereonly in reference to the products or services properly denominated bythe marks to the extent that such trademark rights may exist.)

FIG. 8 is a block diagram of system 800 for ensuring the effectivenessof an overall SDE with respect to target business outcomes. The systemis shown as a closed-loop framework including: optimization sub-system802; SDE 803; modeling module 804; assurance engine 806; orchestrationengine 808; service orchestration module 810; deep introspection module812; deep introspection probes 814 a, 814 b, 814 c; fast workloadmigration applications 816 a, 816 b, 816 c; and fine-grained isolationand quarantine applications 818 a, 818 b, 818 c. FIG. 9 shows flowchart900 depicting a method performed, at least in part, by system 800. Thismethod and associated system will now be discussed, over the course ofthe following paragraphs.

The KPIs of a specified service are continuously monitored and evaluatedat each layer (the application layer and the infrastructure layer), sothat the overall utility function (value of the business operation, costof resource, and risk to potential failures) may be continuouslyevaluated. Processing begins at step S905, where modeling module 804determines the user's utility function based on one or more of: acurrent workload, and a scalable service ecosystem API (applicationprogram interface). Deep introspection probes 814 a, 814 b, 814 c withineach layer, managed by deep introspection module 812, are used tofacilitate both the initial determination and subsequent monitoringactivity (see step S925).

Processing proceeds to step S910, where modeling module 804 determinesthe resource cost function based on the current runtime environment,where the workload(s) and/or service(s) are implemented. The resourcesused by each method have a particular cost. The resource cost functiontakes into account the resources required by each method performed inthe runtime environment. The cost is a function of the particular SDEIaaS abstraction of compute, storage, and/or network. The abstractionmay include: (i) server virtualization; (ii) storage virtualization;and/or (iii) switch fabric virtualization (network). In this example, aunified switch fabric for both server and storage enable assemblingpurpose fit systems and/or programmable infrastructures for dynamicoptimization of the SDE in response to business requirements. Step S910is also facilitated by deep introspection module 812, as discussedabove.

Processing proceeds to step S915, where modeling module 804 determinesthe risk of potential failure(s) and the corresponding cost(s) offailure(s). The risk considered in this step includes the operationalrisk associated with resources becoming unavailable due to data centeroutage, cyber-attacks, and/or cascading failures. Operation risk isdefined as the risk of a change in value caused by the fact that actuallosses, incurred for inadequate or failed internal processes, people andsystems, or from external events (including legal risk), differ from theexpected losses. This definition from the Basel II regulations was alsoadopted by the European Union Solvency II Directive. It can also includeother classes of risk, such as fraud, security, privacy protection,legal risks, physical (e.g. infrastructure shutdown) or environmentalrisks. Specifically, the focus here is on the risk of businessdisruption and systems failures, which includes utility disruptions,software failures, hardware failures, and/or datacenter outages. Therisk of potential system failure is determined by the probability ofsystem failure, and the redundancy of the application, system software,and systems themselves. The overall approach is to have sufficientredundant resources to minimize loss of availability while utilizingminimal amount of resources. To summarize, in the above-mentioned steps,S905, S910, and S915, data identified during monitoring and initialbaseline determination is fed into behavior models of modeling module804 for the SDE (that includes the workload, the data (usage patterns),the infrastructure, and the people and processes).

Processing proceeds to step S920, where the modeling module 804,calculates the expected net utility, or overall utility function, of thesystem. The expected net utility is computed by taking the valueproposition of completed service, or successful service, and subtractsthe resource cost, determined in step S910. Further, an adjustment ismade to the net utility based on the risk of failure, determined in step915.

Processing proceeds to decision step S925, where modeling module 804decides whether the net utility as calculated in step S920 isacceptable, or good. Occasionally, triggering events occur that causeperformance levels to drop. In this decision step, such triggeringevents will be recognized by a reduced net utility. If the net utilityis acceptable, processing follows the “yes” branch, returning to stepS905. If the net utility is not acceptable, processing proceeds to stepS930, where adjustments are considered for improving the net utilitylevel.

Triggering events include, for example: (i) explicit request by theservice; (ii) explicit request by the workload; (iii) deviation of theobserved KPIs of the business operation from the specified tolerance(s)(e.g. according to a service level agreement); and (iv) proactivedetermination of potential catastrophic events (e.g. data center outage,cascading failure, and cyber attacks). The determination cited in (iv)may be based on the continuous behavior models generated by modelingmodule 804 for users, workloads, and/or systems.

Following the “no” branch, processing proceeds to step S930, whereassurance engine 806 applies a decision model to determine a nextconfiguration or otherwise determine a change, or changes, to improvethe net utility level. In this example, the assurance engine processeswhat-if scenarios. What-if scenarios consider, for example, deploymentof different amounts of resources against each task. The what-ifscenarios are evaluated, or re-evaluated, to determine whetherperformance according to the KPIs can be potentially improved.Improvement actions may include: (i) scaling up of the resources foreach task; (ii) scaling down of the resources for each task; (iii)migrating the task; and/or (iv) re-building the task. The what-ifscenario is based on the behavior models that are fit with the datacollected by the monitoring and deep introspection mechanisms.

Processing proceeds to step S935, where orchestration engine 808,initiates the KPI improvement actions determined in step S930. When thescenario that maximizes the overall utility function is selected byassurance engine 806, orchestration engine 808 orchestrates the SDE for:(i) adjusting resource provisioning (e.g. scale up or scale down); (ii)establishing a quarantine of the resources (e.g. in various resiliencyand/or security scenarios); (iii) migrate task and/or workload; and/or(iv) performing server rejuvenation.

Processing may end at step S935, but continuous system improvement isavailable when processing returns to step S905, where the improvementaction drives changes in one or more of: (i) the user's utilityfunction; (ii) the resource cost function; and (iii) the risk ofpotential failures.

Some embodiments of the present invention may include one, or more, ofthe following features, characteristics and/or advantages: (i) providesa framework for a cloud service provider who is providing services formultiple enterprises where each enterprise may utilize multiple cloudservice providers to handle their workloads (consequently, there will betwo separate perspectives, one for each enterprise and one for eachcloud service provider, to be optimized concurrently, though separately;(ii) uses an outcome-optimized framework to ensure preferred performancestandards from the perspectives of both the enterprise and the cloudservice provider; (iii) provides a holistic framework of continuouslyoptimizing the outcome of the overall mapping of business services tothe available virtualized heterogeneous resources while taking intoaccount the cost of resources, cost of failure, and the business valuedelivered by each of the services; (iv) includes modeling and predictionof the workload behavior from each and every service performed in thecomputing environment, in order to perform continuous outcomeoptimization that includes the predicted cost of resources, predictedcost of failure, and predicted value generated by executing each andevery service; (v) provides a framework that is a combination ofworkload specification (and abstraction) and both passive and activemonitoring of the workloads in order to provide a more accurateprediction of the workloads in order to forecast a future condition;and/or (vi) continuously and dynamically provisions resources for all ofthe services executed in the environment, so that the utility (oroutcome) of the overall environment is optimized based on the projectedworkload behavior.

Present invention: should not be taken as an absolute indication thatthe subject matter described by the term “present invention” is coveredby either the claims as they are filed, or by the claims that mayeventually issue after patent prosecution; while the term “presentinvention” is used to help the reader to get a general feel for whichdisclosures herein that are believed as maybe being new, thisunderstanding, as indicated by use of the term “present invention,” istentative and provisional and subject to change over the course ofpatent prosecution as relevant information is developed and as theclaims are potentially amended.

Embodiment: see definition of “present invention” above—similar cautionsapply to the term “embodiment.”

and/or: inclusive or; for example, A, B “and/or” C means that at leastone of A or B or C is true and applicable.

User/subscriber: includes, but is not necessarily limited to, thefollowing: (i) a single individual human; (ii) an artificialintelligence entity with sufficient intelligence to act as a user orsubscriber; and/or (iii) a group of related users or subscribers.

Electrically Connected: means either directly electrically connected, orindirectly electrically connected, such that intervening elements arepresent; in an indirect electrical connection, the intervening elementsmay include inductors and/or transformers.

Mechanically connected: Includes both direct mechanical connections, andindirect mechanical connections made through intermediate components;includes rigid mechanical connections as well as mechanical connectionthat allows for relative motion between the mechanically connectedcomponents; includes, but is not limited, to welded connections, solderconnections, connections by fasteners (for example, nails, bolts,screws, nuts, hook-and-loop fasteners, knots, rivets, quick-releaseconnections, latches and/or magnetic connections), force fitconnections, friction fit connections, connections secured by engagementcaused by gravitational forces, pivoting or rotatable connections,and/or slidable mechanical connections.

Data communication: any sort of data communication scheme now known orto be developed in the future, including wireless communication, wiredcommunication and communication routes that have wireless and wiredportions; data communication is not necessarily limited to: (i) directdata communication; (ii) indirect data communication; and/or (iii) datacommunication where the format, packetization status, medium, encryptionstatus and/or protocol remains constant over the entire course of thedata communication.

Receive/provide/send/input/output: unless otherwise explicitlyspecified, these words should not be taken to imply: (i) any particulardegree of directness with respect to the relationship between theirobjects and subjects; and/or (ii) absence of intermediate components,actions and/or things interposed between their objects and subjects.

Module/Sub-Module: any set of hardware, firmware and/or software thatoperatively works to do some kind of function, without regard to whetherthe module is: (i) in a single local proximity; (ii) distributed over awide area; (iii) in a single proximity within a larger piece of softwarecode; (iv) located within a single piece of software code; (v) locatedin a single storage device, memory or medium; (vi) mechanicallyconnected; (vii) electrically connected; and/or (viii) connected in datacommunication.

Computer: any device with significant data processing and/or machinereadable instruction reading capabilities including, but not limited to:desktop computers, mainframe computers, laptop computers,field-programmable gate array (FPGA) based devices, smart phones,personal digital assistants (PDAs), body-mounted or inserted computers,embedded device style computers, application-specific integrated circuit(ASIC) based devices.

What is claimed is:
 1. A method for outcome-based adjustment of asoftware-defined environment (SDE), the method comprising: establishinga link between a business outcome and a first resource configurationfrom a SDE; establishing a monitoring mechanism for continuouslymeasuring a current state of the SDE; using a behavior model of the SDEto forecast a triggering event; responsive to a forecast of thetriggering event, using the behavior model to determine a secondresource configuration to achieve the business outcome; wherein: thelink includes at least one of a utility of services for the businessoutcome, a cost of a set of resources consumed by the first resourceconfiguration, and a risk of the set of resources becoming unavailable;and at least the using the behavior model steps are performed bycomputer software running on computer hardware.
 2. The method of claim1, further comprising: capturing a range of tradeoffs for achieving thebusiness outcome from the SDE; wherein: the range of tradeoffs make up aset of resource configurations.
 3. The method of claim 2, wherein atradeoff within the range of tradeoffs includes one of tiering of datastorage, tiering of compute resources, placement of processingresources, scaling of compute resources, scaling of storage resources,scaling of network resources, migrating compute resources, migratingstorage resources, and migrating network resources.
 4. The method ofclaim 1, wherein the business outcome is divided into a set ofprioritized tasks, each task having a corresponding set of keyperformance indicators (KPIs).
 5. The method of claim 4, wherein thesecond resource configuration is determined, at least in part, by thebehavior model indicating an improved performance level of a KPI of ahigh priority task when compared to the corresponding performance levelin the first resource configuration.
 6. The method of claim 1, whereininfrastructure is provided as a service in a cloud environment.
 7. Themethod of claim 1, wherein the triggering event is one of: (i) requestby a service; (ii) request by a workload; (iii) deviation of an observedperformance indicator of a business operation; and (iv) a potentiallycatastrophic event.
 8. A computer program product for outcome-basedadjustment of a software-defined environment (SDE), the computer programproduct comprising a computer readable storage medium having storedthereon program instructions programmed to: establish a link between abusiness outcome and a first resource configuration from a softwaredefined environment; establish a monitoring mechanism for continuouslymeasuring a current state of the SDE; use a behavior model of the SDE toforecast a triggering event; and responsive to a forecast of thetriggering event, use the behavior model to determine a second resourceconfiguration to achieve the business outcome; wherein: the linkincludes at least one of a utility of services for the business outcome,a cost of a set of resources consumed by the first resourceconfiguration, and a risk of the set of resources becoming unavailable.9. The computer program product of claim 8, further comprising: programinstructions programmed to capture a range of tradeoffs for achievingthe business outcome from the SDE; wherein: the range of tradeoffs makeup a set of resource configurations.
 10. The computer program product ofclaim 9, wherein a tradeoff within the range of tradeoffs includes oneof tiering of data storage, tiering of compute resources, placement ofprocessing resources, scaling of compute resources, scaling of storageresources, scaling of network resources, migrating compute resources,migrating storage resources, and migrating network resources.
 11. Thecomputer program product of claim 8, wherein the business outcome isdivided into a set of prioritized tasks, each task having acorresponding set of key performance indicators (KPIs).
 12. The computerprogram product of claim 11, wherein the second resource configurationis determined, at least in part, by the behavior model indicating animproved performance level of a KPI of a high priority task whencompared to the corresponding performance level in the first resourceconfiguration.
 13. A computer system for outcome-based adjustment of asoftware-defined environment (SDE), the computer system comprising: aprocessor(s) set; and a computer readable storage medium; wherein: theprocessor set is structured, located, connected, and/or programmed torun program instructions stored on the computer readable storage medium;and the program instructions include program instructions programmed to:establish a link between a business outcome and a first resourceconfiguration from a software defined environment; establish amonitoring mechanism for continuously measuring a current state of theSDE; use a behavior model of the SDE to forecast a triggering event; andresponsive to a forecast of the triggering event, use the behavior modelto determine a second resource configuration to achieve the businessoutcome; wherein: the link includes at least one of a utility ofservices for the business outcome, a cost of a set of resources consumedby the first resource configuration, and a risk of the set of resourcesbecoming unavailable.
 14. The computer system of claim 13, furthercomprising: program instructions programmed to capture a range oftradeoffs for achieving the business outcome from the SDE; wherein: therange of tradeoffs make up a set of resource configurations.
 15. Thecomputer system of claim 13, wherein the business outcome is dividedinto a set of prioritized tasks, each task having a corresponding set ofkey performance indicators (KPIs).
 16. The computer system of claim 15,wherein the second resource configuration is determined, at least inpart, by the behavior model indicating an improved performance level ofa KPI of a high priority task when compared to the correspondingperformance level in the first resource configuration.
 17. A methodcomprising: determining a business operation and a corresponding set oftasks to be performed in a software defined environment (SDE);establishing a first resource configuration to perform the correspondingset of tasks to achieve a business outcome target; determining a firstresource cost for performing the corresponding set of tasks; monitoringthe SDE to identify a triggering event; responsive to identifying thetriggering event, establishing a second resource configuration toaddress the triggering event; and determining a second resource cost forperforming the corresponding set of tasks according to the secondresource configuration; wherein: at least the monitoring andestablishing a second resource configuration steps are performed bycomputer software running on computer hardware.
 18. The method of claim17, further comprising: assigning a priority level to tasks within thecorresponding set of tasks; determining a set of performance indicatorscorresponding to a task having a first priority level; wherein: the stepof establishing the second resource configuration is based, at least inpart, on a performance level of a performance indicator in the set ofperformance indicators.
 19. The method of claim 17, wherein addressingthe triggering event includes one of scaling up a resource in the firstresource configuration for performing a task in the corresponding set oftasks, scaling down a resource in the first resource configuration forperforming a task in the corresponding set of tasks, migrating a task ofthe corresponding set of tasks, re-building a task of the correspondingset of tasks, and re-building the business operation.
 20. The method ofclaim 17, wherein the step of establishing the second resourceconfiguration includes evaluating a set of “what-if” scenarios where aset of multiple resource configurations are applied to a behavior modelof the SDE to identify a best alternative to the first resourceconfiguration, the best alternative being the second resourceconfiguration.